The configuration of the East Rand Basin surface runoff model used for source apportionment studies

Abstract

Numerous mines have been operating in the East Rand Basin (ERB) since the 1940s. Most of these mining activities have since ceased and the mines are busy flooding . If decant of acid mine drainage takes place, treatment options will have to be implemented. A source of major complexity is the fact that these mines have become interconnected over the years. Furthermore, these mines have changed ownership numerous times since mining started. The apportionment of responsibility for the decanting mines has become a major management concern as a legacy issue is created in terms of determining who is responsible for what portion of the environmental degradation. An integrated modelling approach between mine water, groundwater and surface water is required to make predictions surrounding future water quality and quantity; and more importantly, who is responsible and what is the portion of that responsibility for each mine. The focus of this study is only on the development and configuration of an appropriate surface water model of the ERB to be interfaced with existing mine flooding and groundwater models of the area. This includes examining the effect on the flow rate brought about by the wetlands found in the river system of the study area and the incorporation thereof into the surface water model. Through a rigorous reviewing process, it was decided that the Storm Water Management Model (SWMM) would be used as the appropriate modelling platform. Although this model is generally used for urban storm water drainage modelling, it was successfully utilised in this study to model flows in a predominantly natural catchment. Satisfactory model calibration was achieved, although the lack of data necessitated various assumptions in the model setup. The application of the calibrated model for source apportionment is illustrated through the use of an example scenario. With additional data, this model can be utilised to represent the real world situation of the ERB more accurately, thereby providing even better outputs and resulting in the better management of the ERB